Audience platform

ABSTRACT

An audience platform is disclosed. In a first example case, a first question is received. A preference event associated with the first question is received. A score is determined for the first question based at least in part on the preference. In a second example case, indications of a first and second potential interviewee are received. Preference events associated with the first and second potential interviewees are received. Scores are determined for the first and second potential interviewees based at least in part on the received preference events. A designated interviewee is selected based on the first and second scores. In a third example case, indications of a first and second potential awardee are received. Preference events associated with the first and second potential awardee are received. Scores are determined for the first and second potential awardees based at least in part on the received preference events.

CROSS REFERENCE TO OTHER APPLICATIONS

This application is a continuation of co-pending U.S. patent applicationSer. No. 12/543,503, which was filed Aug. 18, 2009, is entitled“Audience Platform” and issued [TBD] as U.S. Pat. No. [TBD], and whichclaims priority to U.S. Provisional Patent Application No. 61/182,745,filed May 31, 2009 and entitled “Audience Platform,” all of which areincorporated herein by reference for all purposes. This application isrelated to U.S. patent application Ser. Nos. 13/781,327, filed Feb. 28,2013, and [TBD; LI-P0093.DIG.C3], both of which are entitled “AudiencePlatform.”

BACKGROUND OF THE INVENTION

Typically, questions posed to political candidates, celebrities, andother interviewees (collectively “individuals”) are formulated by,selected by, or otherwise vetted by an editor or journalist.Unfortunately, such questions may not correspond with the interests ofan audience. And, which individuals should be interviewed or otherwiserecognized, are typically selected exclusively by editors and, again,may not correspond with the interests or opinions of an audience.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of the invention are disclosed in the followingdetailed description and the accompanying drawings.

FIG. 1A illustrates an embodiment of an environment for collecting andmanaging content contributions.

FIG. 1B illustrates an embodiment of an interface to a preferencesystem.

FIG. 2 is a flow chart illustrating an embodiment of a process forreceiving a story submission.

FIG. 3 is a flow chart illustrating an embodiment of a process forreceiving a story submission.

FIG. 4A illustrates an embodiment of a story permalink.

FIG. 4B illustrates an embodiment of an interface to a preferencesystem.

FIG. 4C illustrates an embodiment of an interface to a preferencesystem.

FIG. 5 illustrates an embodiment of an interface to a preference system.

FIG. 6A illustrates an embodiment of an interface to a preferencesystem.

FIG. 6B illustrates an embodiment of an interface to a preferencesystem.

FIG. 6C is a flow chart illustrating an embodiment of a process forrecording a user's preference for content.

FIG. 7 is a flow chart illustrating an embodiment of a process forrecording a preference for a content contribution.

FIG. 8A illustrates an embodiment of a visualization interface.

FIG. 8B illustrates an embodiment of a visualization interface.

FIG. 8C illustrates an embodiment of a visualization interface.

FIG. 8D illustrates an embodiment of a visualization interface.

FIG. 9 illustrates an embodiment of a visualization interface.

FIG. 10 illustrates an embodiment of a visualization interface.

FIG. 11A illustrates an embodiment of a visualization interface.

FIG. 11B illustrates an embodiment of a visualization interface.

FIG. 11C illustrates an embodiment of a visualization interface.

FIG. 12A is an example of a content contribution.

FIG. 12B illustrates an embodiment of an interface to a preferencesystem.

FIG. 12C illustrates an embodiment of an interface to a preferencesystem.

FIG. 13A illustrates an embodiment of an interface to a preferencesystem.

FIG. 13B illustrates an embodiment of an interface to a preferencesystem.

FIG. 14 illustrates an embodiment of an interface to a preferencesystem.

FIG. 15 illustrates an embodiment of a process for processing questions.

FIG. 16 illustrates an embodiment of an interview permalink.

FIG. 17A illustrates an embodiment of a portion of an interviewpermalink.

FIG. 17B illustrates an embodiment of a portion of an interviewpermalink.

FIG. 18 illustrates an embodiment of a portion of an interface to apreference system.

FIG. 19 illustrates an embodiment of a process for selecting aninterviewee candidate.

FIG. 20 illustrates an embodiment of a candidate selection page.

FIG. 21 illustrates an embodiment of a process for selecting an awardeecandidate.

FIG. 22 illustrates an embodiment of a third party website.

FIG. 23 illustrates an embodiment of an interface to a preferencesystem.

DETAILED DESCRIPTION

The invention can be implemented in numerous ways, including as aprocess; an apparatus; a system; a composition of matter; a computerprogram product embodied on a computer readable storage medium; and/or aprocessor, such as a processor configured to execute instructions storedon and/or provided by a memory coupled to the processor. In thisspecification, these implementations, or any other form that theinvention may take, may be referred to as techniques. In general, theorder of the steps of disclosed processes may be altered within thescope of the invention. Unless stated otherwise, a component such as aprocessor or a memory described as being configured to perform a taskmay be implemented as a general component that is temporarily configuredto perform the task at a given time or a specific component that ismanufactured to perform the task. As used herein, the term ‘processor’refers to one or more devices, circuits, and/or processing coresconfigured to process data, such as computer program instructions.

A detailed description of one or more embodiments of the invention isprovided below along with accompanying figures that illustrate theprinciples of the invention. The invention is described in connectionwith such embodiments, but the invention is not limited to anyembodiment. The scope of the invention is limited only by the claims andthe invention encompasses numerous alternatives, modifications andequivalents. Numerous specific details are set forth in the followingdescription in order to provide a thorough understanding of theinvention. These details are provided for the purpose of example and theinvention may be practiced according to the claims without some or allof these specific details. For the purpose of clarity, technicalmaterial that is known in the technical fields related to the inventionhas not been described in detail so that the invention is notunnecessarily obscured.

FIG. 1A illustrates an embodiment of an environment for collecting andmanaging content contributions. Users, such as user 104, submit content(hereinafter a “story contribution” and a “third party news articlecontribution”) to preference system 102. In the example shown, contentis submitted in part by providing to preference system 102 the uniformresource locator (URL) of a story, such as a story found on web page106.

Preference system 102 includes a web module 108 that provides typicalweb server functionality such as serving website 116, capturing userinput, and providing Really Simple Syndication (RSS) feed (110) support.In the example shown, web module 108 is an Apache HTTP server thatsupports running PHP scripts. Web module 108 is interfaced with adatabase 112, such as through a MySQL® database backend.

As described in more detail below, users are made aware of the submittedcontent through website 116 and features such as RSS feeds. In additionto providing a link to the content (e.g., a hyperlink to web page 106)and information such as a summary of the story and the date and time itwas submitted, website 116 permits users to indicate their preferencesfor the content by making a variety of interactions. For example, userscan “digg” a story to indicate their like of its content, “bury” a storyto indicate problems with the content, and may also take other actionssuch as commenting on the content. These actions (including the initialsubmission of the content contribution) are referred to hereincollectively as “preference events.”

Whenever a preference event occurs (e.g., whenever a user submits,diggs, buries, or comments on content), the event is recorded indatabase 112 along with associated information such as the identity ofthe user and a time/date stamp. As described in more detail below,information recorded in database 112 is used in a variety of ways, suchas in conjunction with visualization tools that query database 112and/or make use of data extracted from database 112.

In some embodiments, the infrastructure provided by portions ofpreference system 102 is located on and/or replicated across a pluralityof servers rather than the entirety of preference system 102 beingco-located on a single platform. Such may be the case, for example, ifthe contents of database 112 are vast and/or there are many simultaneousvisitors to site 116.

FIG. 1B illustrates an embodiment of an interface to a preferencesystem. The example shown is an implementation of a portion of website116, as rendered in a browser. A user, known as “Alice” is logged intosite 116. Interface 150 includes a sidebar 152 that provides access tovarious system services. For example, by selecting region 154 of sidebar152, Alice is presented with an interface that permits her to view herprofile and manage account settings such as her current email addressand password; view previous preference events she's taken (her“history”); and access friend-related features described in more detailbelow. Region 156 provides an indication of whether Alice has anymessages and will present her with an interface to a message system(such as a mailbox) if selected. As described in more detail below, byselecting region 158, Alice will be presented with an interface throughwhich she can submit a news story for inclusion on system 102.

Region 160 displays a list of categories into which news stories aregrouped. If “View All” is selected, stories from all categories will bedisplayed in story window 164. As shown, the “Technology” category isselected. In some embodiments, visual indications of what category isselected are presented. In the example shown, the selected category ishighlighted (represented here by stippling) at 166, and the title of thecategory appears above story window 164 at 168. In some embodiments,Alice can configure which topics are available to her on site 116. Forexample, if Alice dislikes Sports, she can configure interface 150 tonever show her any sports-related stories, even when viewing using the“View All” option.

Story window 164 typically includes one or more story entries 170. Inthe example shown, a story entry includes the title of a story, as wellas other associated information, such as who submitted the story andwhen, the external URL of the story, the category to which the storybelongs, and a summary of the story. As described in more detail below,links are provided to the story directly (such as by clicking on thetitle), as well as to an area of site 116 associated with the story,referred to herein as the story's permalink. For example, by clicking onthe comments link (176) of the story, Alice will be presented with thecomments portion of the permalink described in more detail below.

Story entry 170 also includes a problem reporting region 178. Users mayreport problems for a variety of reasons. For example, the first storyentry and the third story entry shown describe the same news—scientistssuperheating a gas. Alice has selected the problem, “duplicate” story,from problem reporting region 178. As described in more detail below,this is one form of burying a story. In some embodiments, buried storiesare displayed differently, or removed entirely from the user'sinterface. In the example shown, once a story is buried, it is greyedout, represented here by stippling (180).

As described in more detail below, each story has one or more scoresassociated with it. In the example shown, the “digg” score (172) foreach story is displayed, as is an interactive region beneath the score(box 174) that allows a user to “digg” the story. The first story hasbeen dugg 237 times, but has not been dugg by Alice. As described inmore detail below, if Alice were to select region 174, a variety ofactions would be immediately taken, including increasing the digg scoreof the story and updating the region's text from “digg it” to “dugg!,”as shown in region 182.

Alice is currently viewing a “promoted stories” (184) view of storywindow 164. This means that all of the stories presented to Alice on thecurrent view of the interface have exceeded a promotion threshold. Oneexample of a promotion threshold is the raw number of diggs. Otherrequirements/factors may be used for thresholding in addition to orinstead of a digg score, such as requiring that a certain amount of timeelapse between story submission and story promotion, the speed withwhich stories are being dugg, information associated with users thathave dugg the story, etc. Because some threshold of users must agreethat a story has merit before being promoted, stories shown in promotedview 184 are unlikely to contain spam or otherwise be inherentlyinappropriate for Alice's viewing.

In some embodiments, different thresholds are used for differentstories, such as for stories in different categories. For example, thepromotion of a math-related story may only require 100 diggs whereas astory about the president may require 500 diggs.

If Alice selects the upcoming stories tab (186), only stories which havenot yet met the appropriate threshold will be displayed. For example,newly submitted stories which have not yet been “dugg” by a sufficientnumber of people will be presented by selecting tab 186. In someembodiments, if a story languishes in the upcoming stories pool for morethan a certain period of time without receiving a sufficient digg scoreto be promoted (e.g., for a week), the story is removed from the pooland can only be found via its permalink or through a search. In someembodiments, such stories are deleted from database 112. Such storiesare typically indicative of spam, inaccuracies and old news. Similarly,if enough users bury a story, the story may be removed from the pooland/or database 112.

In other embodiments, other views of stories may be presented asapplicable, such as a view that unifies both the promoted and theupcoming stories. In the example shown, because Alice has selected the“Technology” category (166), only technology related stories arepresented in the promoted stories (184) and upcoming stories (186)views. Similarly, the topics of the presented stories (e.g., “Math,” areall subtopics of Technology). In some embodiments, the informationpresented with the story entry may vary, such as from topic to topic.For example, if Alice selected “View All” at 160, the listed topic maybe the top level category to which the story belongs (e.g.,“Technology”) or include a drilled down description (e.g., “WorldNews—Canada—Elections”).

As described in more detail below, portion 162 of interface 150 displaysthe recent activities (preference events) of Alice's friends. Forexample, in the last 48 hours, Alice's friends have submitted twostories, dugg twelve stories, and commented on sixteen stories, asreflected in dashboard 162. Of the twelve stories her friends have dugg,four of the stories have not yet been promoted. In some embodiments,assorted visual cues of her friends' activity are presented throughoutwebsite 116. In the example shown, stories dugg by Alice's friends arenotated by a banner (184) placed across the digg score. In other cases,other cues may be used, such as by changing the color of the story,and/or interactive behavior such as playing a sound or showing thefriend's avatar icon when, for example, Alice's cursor hovers over astory dugg by a friend.

Region 188 displays a list of tools, such as visualization tools, thatAlice can use to view and interact with content and/or preferenceevents.

Story Submission

FIG. 2 is a flow chart illustrating an embodiment of a process forreceiving a story submission. This process may be implemented onpreference server 102. In the example shown, the process begins at 202when information associated with a story is received. For example, insome embodiments at 202, information such as the URL of a story and asummary of the story located at that URL is received.

At 204, one or more checks are performed. As described in more detailbelow, examples of checks include checking to make sure the URL is validand does not, for example, contain a typo; checking for duplicatestories; determining whether the story submission appears on a blacklistor is otherwise to be blocked; determining whether the story is beingsubmitted by a blacklisted user; determining whether the story is beingsubmitted by an anonymous proxy, etc. At 206, it is determined whetherthe story should be accepted.

In some embodiments, if the story submission fails any of the checksperformed at 204, the story is rejected at 210. In some embodiments, athreshold is applied to determine whether or not a story is accepted at208. For example, a story that appears to be a duplicate may be flaggedfor review by an administrator, may be provisionally marked as apotential duplicate, may be accepted so long as no other checks arefailed, etc. In some embodiments, the identity of the submitter is takeninto consideration when determining whether to accept a story. Thedecision of whether to accept the story may be based at least in part onfactors such as the length of time the user has been a registered userof site 116, whether the user has previously submitted inappropriatecontent, and/or a score assigned to the user.

Typically, the information received at 202 is received through a webinterface, such as a story submission form that can be accessed, byselecting region 158 of interface 150. Other methods of submission mayalso be used, as appropriate. For example, an external website, such asa user's blog, could be configured to provide an interface to server102. Submission may also be automated, such as by syndicating a newsfeed to a story submission component executing the process shown in FIG.202. As described in more detail below, submissions of the informationreceived at 202 can also occur through the use of an application programinterface (API), browser plugin, etc.

FIG. 3 is a flow chart illustrating an embodiment of a process forreceiving a story submission. In the example shown, the process isimplemented on preference server 102 and is an example implementation ofthe process shown in FIG. 2. The process begins at 302 when anindication that a story is being submitted is received. Suppose Alicewishes to submit a story. When she selects region 158 of interface 150,server 102 is notified at 302.

At 304, it is determined whether the submitting user is logged into site116. If not, the user is presented with a page at which he or she cancreate an account or log in to an existing account. After completingregistration and/or logging in, the user is directed back to the storysubmission interface (not shown).

A logged in user, such as Alice, is then presented with an interfacethrough which a story may be submitted, such as a web form. At 308, aURL is received, such as via Alice entering the URL into the form.

System 102 maintains a block list that includes URLs that, for example,have been reported by administrators as spam sites, fraudulent sites,etc. If a threshold number of users report a story (such as throughregion 178 of interface 150), the story may be automatically added tothe block list. At 310 it is determined whether the URL is present onthe list of blocked URLs. In some embodiments, instead of or in additionto maintaining a list of blocked URLs, system 102 checks for blockedURLs in conjunction with a third party, such as a commercial anti-spamregistry. If the submitted URL appears on the blocked list, the user ispresented with an error at 312. In various embodiments, the errorindicates to the user the problem with the URL, such as that the URLbelongs to a known spammer. In such cases, the user may be presentedwith the option of challenging the block. In other embodiments, a usersubmitting a blocked URL is not told why the URL is blocked, or may notbe told that the URL is blocked at all. For example, a spurious “systemconfiguration” error may be presented to the user to help minimizeattempts at circumventing checks.

At 314, it is determined whether the URL can be reached. One way ofperforming this check is to make use of a tool such as curl or wget. Ifthe URL cannot be reached, for example because of a typo (e.g., HTTPStatus Code 404) or because accessing the URL requires a login/password(e.g., HTTP Status Code 401), the user is presented with an error at316. In various embodiments, the user is permitted to revise andresubmit a failed URL without having to restart the process at 302.

Duplicate checking is performed on the URL at 318. In some embodiments,the check performed looks only for exact matches of the URL. In otherembodiments, fuzzy or other matching is applied.

If it is determined that the submitted URL is a duplicate of, or similarto, a URL previously submitted to server 302, at 320 the user ispresented with a list of the previously submitted story or stories. Insome cases, the new story submission is a duplicate of an existing storysubmission. In other cases, however, the stories may be distinct,despite sharing a common URL. Such may be the case, for example, with acorporate website that always posts new press releases to the same URL,such as “www.company.com/news.html.” Suppose Alice submits a URL that isalready stored in database 112. At 320 she is asked to compare her storyagainst the other story or stories submitted under that URL (324). Forexample, the interface may present to her a list of the existing storiesmatching her submitted URL in a format similar to story window 164 shownin FIG. 1B. If the story she wishes to submit has already beensubmitted, she can digg the existing story (326) rather than submit aduplicate. If her story is not a duplicate, she can continue with thesubmission. In various embodiments, considerations such as thesophistication of the user determine whether an exact duplicate URL willbe permitted or whether the user will be forced to digg one of thestories presented on the duplicate list instead of submitting the newstory submission.

At 322, the user is prompted to supply additional information about thestory submission, such as the story's title, a summary of the story, andto which category or categories it belongs. In some embodiments, theinformation collected at 322 is received at the same time that the URLis received (308) and portion 322 of the process shown in FIG. 3 isomitted.

At 328, additional checks are performed on the story. For example, aspam story may escape detection at 310. Such may be the case if the spamwas recently created or is an attempt to unscrupulously drive traffic toa previously legitimate page and is not already present in a blacklist.One check that can be performed at 328 includes applying spam detectiontechniques to the text located at the submitted URL and/or the title orsummary provided by the user. Additional checks may also be employed inaddition to or instead of spam checks at 328. For example, adetermination may be made of whether the submitter (e.g., Alice) isconnecting to site 116 via an anonymous proxy. If it is determined at328 that the submission is spam or should otherwise not be accepted, at330, the submission is rejected. In some embodiments, the submission is“silently” rejected—the user is shown a “successful” dialogue when, infact, the story is rejected. In other embodiments, the user is presentedwith an error, such as the error presented at 312.

Additional duplication checks are performed on the story at 332. In someembodiments, the submitted title and summary of the story are comparedagainst the titles and summaries of stories already submitted to server102. In some embodiments, the page is crawled and a full text match(such as a MySQL® full text search) is performed against the submittedstory and previously submitted stories. In such a case, database 112 isconfigured to store at least portions of the crawls in addition toinformation associated with the story. If it is determined that thestory is a potential duplicate, at 334 the user is presented the optionof digging the story (336) or submitting it anyway.

When a story is accepted at 338, an entry for the story submission iscreated in database 112. Information such as the submission time and theuser who submitted the story are stored, and counts associated with thestory, such as its digg score, are set to zero. The story becomesaccessible in the upcoming stories view (e.g., 186 of FIG. 1B).

Information in one or more tables 114 is also updated to includeinformation associated with the new story, for example for use inconjunction with searching and with visualizations discussed in moredetail below. Additionally, information associated with the submittinguser is modified as appropriate. For example, a count of the number ofstories submitted by the user is incremented, and the story is madeavailable in areas such as the user's profile and the profile areas ofthe user's friends, if applicable.

As described in more detail below, a permalink for the story can beaccessed by visitors to site 116 and contains content assembleddynamically from the information stored in database 112. In system 102,the permalink's URL is created by stripping disallowed characters (suchas punctuation) from the submitted story's title and appending digits asnecessary to avoid collisions. So, for example, if Alice's submittedstory were titled “New Species of Bird Discovered,” once accepted at338, information associated with the submitted story would be accessibleat the URL“http://www.digg.com/science/New_Species_of_Bird_Discovered.html.”

Also at 338, if the user has specified blogging information, such as ausername and password of an account on a blogging service, the submittedstory is posted to the user's blog. Information such as the summaryand/or title of the story can be automatically copied into the blogsubmission and/or edited by the user prior to submission. For example,if Alice has specified the details of her blog account in her profile(reachable by selecting portion 154 of interface 150), when submittingstory submissions, she can specify whether she'd like the story to alsoappear in her blog. If Alice has not configured her blog settings, theability to blog can be greyed out, hidden, and or explained at 338, asapplicable.

Recording and Reflecting Preference Events

FIG. 4A illustrates an embodiment of a story permalink. The exampleshown is an implementation of a portion of website 116 as rendered in abrowser. Story 402 was recently submitted to server 102 (26 minutesago), through the process depicted in FIG. 2. When Alice visits thepermalink of story 402, topic region 160 of sidebar 152 automaticallyexpands and highlights the topic with which story 402 is associated (inthis case, “Science”). The story was submitted by David, who also duggthe story. Alice has David listed under her profile as her friend. As aresult, the digg count includes a visual indication 404 that story 402was dugg by a friend. In some cases, Alice and David know each other andhave each other, mutually, on their list of friends. In other cases, therelation may be one-sided. For example, David may be a columnist orfamous personality whose opinion Alice values.

The digg score of story 402 is currently two (404) and the story has notmet the threshold(s) required for the story to be promoted out of the“upcoming stories” area.

In the interface shown in FIG. 4A, Alice can click digg box 406 toindicate her preference for the story. In some embodiments, additionalactions are taken when Alice diggs a story. For example, if she hasconfigured her blog settings, Alice can specify that stories that shediggs be posted to her blog as she diggs them. Similarly, Alice canconfigure her personal website (e.g., with a JavaScript) toautomatically syndicate recent activities taken in response to stories.

She can report a problem with the story (bury it) by selecting an optionfrom problem dropdown 408. Story reporting options include “duplicate”story (to report that story 402 is a duplicate of another story), “badlink” (to report that the link to the full text of the story isdefective), “spam” (to indicate that the story is fraudulent or spam),“inaccurate” (to indicate that there are factual problems with thestory), and “old news” and “this is lame” to indicate that the story isnot newsworthy. In some embodiments, bury events are anonymous site-wideand are not replicated, for example, in a user's publicly accessibledigging history. One reason for this is to minimize the chance of a“flame war” occurring, such as when a well known user negatively rates astory or comment, for example.

As described in more detail below, region 410 displays comments thatusers have made about story 402. Thus far, a total of five comments havebeen left about story 402, two of which were left by Alice's friends.Alice can submit comments by entering information into region 412 ofFIG. 4A.

In region 414, Alice is currently viewing a list of all the users whodugg story 402. Suppose David is Alice's friend, but Legolas is not. IfAlice selects friends tab 416, the view in region 414 will change toshow only David's name and avatar icon.

In region 418, Alice is currently viewing a list of the users who haveblogged story 402. Charlie is the only person who has blogged the storyso far and he is not Alice's friend. Therefore, if Alice were to selectfriends tab 420, no names would be shown.

Alice can submit this story to her own blog by entering optional text inregion 422 and selecting region 424. Alice can email the story to one ormore addresses by entering them into region 426 and selecting region428.

As shown, all of the information associated with a particular story(e.g., title/summary of the story, digg score, comments, who has bloggedthe story, etc.) is displayed on a single page. In other embodiments,the information is presented across multiple pages, such as with atabbed view with one or more tabs for each component.

FIG. 4B illustrates an embodiment of an interface to a preferencesystem. The example shown is an implementation of portion 410 of website116, as rendered in a browser. In the example shown, Alice has just duggstory 450 by selecting region 452. As a result, rather than a “digg it”message appearing in region 452, a “dugg!” message is displayed. Also asa result of having dugg story 450, a new region (454) is presented toAlice, asking whether she would like to mark the story as a “Favorite.”If Alice selects the “Favorite” region (e.g., by clicking on it), story450 will be listed as a favorite in Alice's profile, discussed in moredetail below. In some embodiments, rather than displaying a separate“Favorite” region 454 after Alice diggs a story, instead of a “dugg!”message, a “Favorite?” message is displayed in region 452. If Aliceclicks on region 452 again, story 450 will be listed as a favorite inAlice's profile. In such an embodiment, Alice is thus able to interactwith region 452 twice—once to “digg” the content, and again to designatethe dugg content as being a favorite.

In some embodiments, rather than or in addition to specifying afavorite, users can designate content as being a “least favorite,” “mosthated,” or any similar strongly negative preference.

Favorites can also be specified relative to periods of time. Forexample, a user may be allowed to designate a favorite of the day, or afavorite of the week/month/etc. If the user updates the favorite duringthat time period, the newly-designated favorite becomes the favorite ofthe day/week/month until the end of the day/week/month until theday/week/month ends. Once the unit of time has ended, the favorite issaved as (e.g., “last week's favorite”).

FIG. 4C illustrates an embodiment of an interface to a preferencesystem. The example shown is an implementation of a portion of website116 as rendered in a browser. In the example shown, stories 476 and 478concern the ACME Tigers, Alice's favorite sports team. A rumor existsthat ACME' s quarterback cheated during a recent game. Alice does notbelieve that the quarterback cheated and is very upset by any suggestionto the contrary. Alice agrees with the content in story 476, but doesnot agree with the content in story 478 and decides that she would liketo bury story 478—not because of a subject-agnostic reason, such as thatthe story is a duplicate or includes advertising, but because she holdsvery strong, personal beliefs, about the subject matter.

She moves her mouse pointer to the bury link (e.g., 472 in the case ofstory 476) of story 478 (not shown) and hover box 474 appears. Alice canbury the story without giving a reason by clicking on the “just bury”portion of the box. Alice can also provide a reason for her bury byselecting one of the options shown. If Alice buries the story byclicking on the “just bury” text, a database entry will be madereflecting that Alice has chosen to bury the story but given “no reason”(e.g., a default value), and Alice's bury may or may not contributetoward whether the story is removed from the site (e.g., based on howmany other “default” buries have been received, and factors such as howlong Alice has been a registered user of the site, what category thecontent is in, and so on). If Alice selects one of the other options,that information will also be reflected in a database entry (and maycount differently when determining whether to remove the story). Buriedstories are viewable from Alice's profile (e.g., via a “My BuriedStories” tab), and may be unburied by Alice if desired.

The bottom option shown in box 474, “Hate It” is different from theother optional reasons for burying content. If Alice selects thatreason, e.g., by clicking on it, Alice performs what is referred toherein as a “placebo bury.” A placebo bury appears to Alice to be nodifferent than a “spam” bury or a “duplicate” bury. For example, if sheselects “Hate It,” story 478 will be removed from her display, and belisted as having been buried by her in her profile. However, noadditional actions will be taken with respect to the story and otherusers' ability to access it. The placebo bury allows users to expresstheir (potentially extreme) personal dislike of certain content withoutimpacting others. Typically, a user enraged enough to “hate” a story isunlikely to hold an objective view about the merits of the story withrespect to other users (e.g., the newsworthiness of the content). Insome embodiments, after performing a placebo bury, Alice is presentedwith the ability to designate the story as her “least favorite” and thetechniques described in conjunction with FIGS. 4B, 6B, and 6C areadapted to accommodate Alice's designation accordingly.

In various embodiments, the options provided in box 474 vary based onfactors such as the category and type of the content. For example, forsports news articles, “Hate It,” and “They Suck!” might both be providedas placebo options. Different placebo text and numbers of placebooptions might be presented in celebrity and politics sections. In thecase of restaurants, books, music, and other types of content that arecategorized by genre, examples of placebo options include “Not MyStyle,” and “Not My Thing,” allowing the user to indicate that hedoesn't like ABC Restaurant because he doesn't like French food—notbecause the food at ABC Restaurant was improperly prepared or theservice was lacking, and without impacting a score or rating of therestaurant/book/music. Further, in the case of some content, such asrestaurants, a “Hate It” bury may contribute to the score of therestaurant and not be used as a placebo option.

As another example, some individuals hold very strong beliefs aboutcompanies, such as manufacturers of cola, computer manufacturers, andcar companies. An example of a non-placebo option for burying a productis “Mine Broke,” which would allow a user to indicate that the productwas flimsy. An example of placebo option for burying a product is “JustDon't Like it,” which a user that doesn't like the color of the productor has another non-functional issue with the product can use withoutimpacting the digg count or other ratings of the product.

In the case of video clips and photographs, examples of placebo optionsinclude “I am offended by this,” and “I don't get it.” In someembodiments the selection of placebo options by users is used todetermine a rating or score for the content. For example, suppose avideo receives several “I don't get it” buries, but also receivesseveral diggs. A rating of the film across all voters can be tabulatedby combining the indications of the two groups of users.

FIG. 5 illustrates an embodiment of an interface to a preference system.The example shown is an implementation of portion 410 of website 1106,as rendered in A browser. In the example shown, Alice is viewingcomments associated with a story. The story currently has eight comments(502), sorted by date. A threshold of −4 diggs or higher has also beenapplied (518). Thus, comment 516, which has been buried 75 times, ishidden. In the example shown, only the header of a buried comment isdisplayed, along with a link to reveal the hidden comment (522).Additionally, the header of comment 516 is greyed out to help a uservisually distinguish between buried and nonburied comments.

Comment 504 was written by Bob, one of Alice's friends, as was comment506 (written by David). In this example, comments written by friends aredistinguished from other comments, such as through having a differentlycolored header. Comments dugg by friends are also distinguished. Thus,while CharlieB is not Alice's friend, his comment (508) is distinguishedbecause it was dugg by Bob, who is Alice's friend, as also indicated bythe inclusion of Bob's name and a star on the header of comment 508. Thenumber of comments left by and/or dugg by her friends is indicated at514.

In the example shown, Bob has written an informative comment, which 18people have dugg. If desired, Alice can digg or bury Bob's comment byselecting the appropriate icon at 520. In the example shown, the diggicon is a green thumb pointing up. The bury icon is a red thumb pointingdown. As described in more detail below, if Alice selects one of theicons, Bob's comment score is immediately updated and the thumbs aregreyed out to indicate to Alice that she's already registered herpreference for Bob's comment.

Suppose Alice finds comment 510 to be off topic or otherwise unhelpful.If she chooses to bury the comment, in the example shown, a variety ofchanges will occur in the interface immediately. The comment score forcomment 510 will decrement by one point. Additionally, comment 510 willcollapse down to just the header, which will grey out. If Alice findsthe poster of the comment, Legolas, a sufficient nuisance, she can blockhim by selecting block icon 524. In this example, if Alice selects theblock icon, she will never be shown any content from Legolas again,site-wide, unless she later chooses to unblock him, such as throughsettings in her profile. Thus, by selecting block icon 524, Alice willnot see comments made by Legolas, stories posted by Legolas, etc.,unless and until she chooses to unblock him.

In some embodiments, if enough people bury a comment, the comment isremoved from the site and/or reported to an administrator. Similarly, ifenough people block a user, in some embodiments the user is reported toan administrator and/or banned from accessing site features.

If desired, Alice can submit one or more comments of her own. Forexample, she may reply to an existing comment by selecting the replybutton associated with the comment (526), or create a new comment bysubmitting text through region 528. In some embodiments, Alice is givena portion of time during which she may edit the comment, such as withinfive minutes of submitting the comment.

As described in more detail below, when Alice submits or diggs acomment, that preference event is recorded in database 112, her profileand the profiles of her friends are immediately updated, and associatedRSS files are updated.

FIG. 6A illustrates an embodiment of an interface to a preferencesystem. The example shown is an implementation of a portion of website116 reached by selecting region 154, as rendered in a browser. In thisexample, Alice is viewing her profile (hereinafter “interface 602”),which has been subdivided into several tabbed views (604-610). A profileprovides access to a variety of information, some of which may bepublicly viewable, and some of which may be kept private. For example,Alice can change account settings, such as her email address andpassword, by selecting portion 604 of interface 602. Visitors to Alice'sprofile will be presented with a subset of the information available toAlice. For example, while Alice sees tab 604 being labeled“Profile+Settings,” a visitor to Alice's profile would see tab 604 asleading to Alice's “Profile” only. Similarly, tab 608, which allowsAlice to add and remove friends, is only available to Alice and ishidden from visitors to her profile. Alice can also add friends byvisiting other users' profiles and selecting an “add this user as myfriend” option located in the profile.

Alice has currently selected to view her friends' history by selectingportion 610 of interface 602. The information presented can be furthercustomized by selecting from subsets of information. For example, ifAlice selects portion 620 of interface 602, she will be presented with alisting of all of the stories that have been dugg by at least one of herfriends. If she selects portion 622, she will be presented with a listof stories that have been dugg by at least one of her friends but havenot yet been promoted. If she selects portion 626, Alice will bepresented with a list of stories submitted by her friends, and byselecting portion 628, Alice will be presented with a list of storiesthat have been commented on by her friends. Other information (notshown) may also be presented in other embodiments, such as a list ofcomments that Alice and/or her friends have dugg.

In the example shown, Alice has selected to view stories “agreed on” byher friends (624). Each of the stories listed in this view have beendugg by at least three of Alice's friends. In various embodiments, Alicecan configure the threshold and specify such information as the numberof friends (or total number of diggs) required for a story to be agreedupon and/or define particular individuals whose digg is necessary for astory to be considered agreed upon, keywords that must be present in thestory, etc. By making use of the “agreed on” view, Alice can readilydiscern the most important stories, even if she has thousands offriends. (I.e., if she sets the threshold to “agreed on by at least 10friends,” and has 1000 friends, the number of stories she is presentedwith is likely to be manageable and especially relevant or interesting.)

Region 616 of interface 602 indicates that four of Alice's friends havedugg story 632. Alice can also see which of her friends have dugg story632 by hovering her input device over the digg score box of story 632.In some embodiments, Alice can interact with region 616, such as bybeing presented with a dialogue that offers to send an email to all ofher friends listed in the region.

By selecting portion 606 of interface 602, both Alice and visitors toAlice's profile will be presented with Alice's history in a formatsimilar to that currently shown, but limited to activities taken byAlice. Additionally, Alice may “undigg” stories and comments that shepreviously dugg by visiting her history.

All of the views described in conjunction with FIG. 6, such as stories“Agreed On” by Alice's friends, can by syndicated as RSS feeds byselecting RSS link 614 on the appropriate page view. In someembodiments, profile visitors (including Alice) are presented with theoption to search (630) all of site 116 for content (634), search Alice'sdiggs for content (636) and/or search diggs made by Alice's friends forcontent (638).

When a user takes certain actions, such as digging a story or burying acomment, the results of that action are reflected immediately, withoutthe user being directed to a “success” page or the appearance of, e.g.,a page refresh occurring to the user. For example, suppose Bob haslisted Alice as his friend. Whenever Alice submits a new story, that newstory immediately appears on Bob's “Friends—Submitted” list and iswritten to the associated RSS file. Similarly, whenever David commentson an article, that fact is immediately reflected under Alice's tab 628as shown in FIG. 6A. As described herein, pages served by web module 108include Asynchronous JavaScript and XML (Ajax) components. Othertechniques may also be used to dynamically update site 116 as renderedin a browser, as appropriate.

FIG. 6B illustrates an embodiment of an interface to a preferencesystem. In the example shown, Alice is viewing a list of items that shehas designated as being her favorite (e.g., by selecting region 454 inFIG. 4B). Alice can designate additional content, such as recentlyviewed content, as favorite by selecting the appropriate region (658) inher profile.

In some embodiments Alice can have a single favorite item at any giventime listed in her profile, also referred to herein as “My #1,”indicating that the item is Alice's #1 favorite item. In otherembodiments, Alice can have a single favorite item per category (e.g.,favorite sports story, favorite politics story) or per type of item(e.g., favorite restaurant, favorite video, favorite news item, favoritepodcast). In any of the above cases, if she subsequently marks as“favorite” another item, the newly selected item will replace thecorresponding existing favorite item in Alice's profile. Itemspreviously designated as “#1” are noted in an archive of “#1” items thatcan be accessed (e.g., by following a link 652).

In some embodiments, Alice can designate multiple favorites, in allcategories/types of content, and a rolling list of the most recentdesignations is displayed in her profile, with older favoritesaccessible via link 652.

In various embodiments the history of Alice's favorites is color coded.For example, more recent favorites are green and older ones are red.Other visual indicators may also be used. For example, the more usersthat have the same content designated as favorite, the brighter thedesignation appears. If many users all have the same content designatedas favorite right now, that content is “hot” and appears with flamesaround it in the “Favorite” section of Alice's profile. If only a fewpeople have that content marked as a favorite, the content may be icycold as indicated by a blue color scheme.

Alice can remove her “favorite” designation of content by selectingregion 656. For example, suppose Alice designated a particular MP3player (one that she owns) as a favorite. The MP3 was actually of poorquality and subsequently broke. Alice does not want other users to thinkthat she still approves of it, so she removes the favorite designation.If instead of breaking, Alice merely received a newer, better player,she may wish to retain the favorite designation for the old player, andalso mark as favorite her new player, so that other users know that shelikes both players. In some embodiments, if Alice undiggs a particularcontent, any favorite designations that she may have made with respectto that content are automatically removed.

Alice can also view the favorite content of her friends (and otherusers) by visiting their respective profiles and selecting a “favorites”tab. Alice can also perform a user search to find other users withsimilar favorites to discover new friends, and/or to discover newcontent. For example, Alice could designate a particular restaurant asher favorite and then perform a search to determine “where people whoalso like my #1 restaurant buy books?” Alice could designate a movie asbeing her favorite and then determine “what news stories are people whoalso share my favorite movie reading now?”

Alice can also see which content she and her friends have commonlydesignated as favorite, such as through information displayed in region654. In some embodiments Alice can also see the aggregate favorites ofher friends by selecting a “see my Friends' #1s” link within her ownprofile, which in turn shows one favorite per friend, such as the itemmost recently designated as favorite by that friend. The aggregate viewis customizable, and also allows Alice to sort the favorites by thenumber of friends who at one point in time (or currently) also havedesignated the content as a favorite.

Statistics on the favorite content of users site-wide is tracked and canbe displayed according to different periods of time, different groups ofusers, different categories/types of content/etc. For example, Alice canview “the content most often designated as favorite of all time,” searchfor “the most frequently #1 restaurant [bar, dry cleaner] in Chicago [ora zip code, or an area code],” see “the product with the most favoritedesignations right now,” search for “the MP3 player with the most #1designations between December 1 and January 31 of last year,” find “the#1 fiction book as designated on the lists of female users between theages of 13 and 25,” and so on. A “top ten” list of favorite content canalso be displayed, e.g. showing the relative positions of content basedon the number of favorite designations, such as “this story is currently#3 in the ranking, up from #6 last week.”

Time-based information can also be used to indicate the “staying power”of the favorite designations for content. For example, if many peopleleave the same content at the top of their favorite list beforereplacing it with other content, this statistic can be measured,searched for, etc. Examples include a search for “the content with thelongest average streak of being a user's favorite content,” “the contentthat, once designated as a favorite, remains a favorite the least amountof time,” and so on.

Favorite content can also be analyzed to determine particular topics orsubjects of interest to a user. For example, suppose Alice designates asfavorite a photograph of the fictional town of Springfield, a video clipof The Simpsons television show, and a news article about a chain ofconvenience stores redecorating with a Simpsons theme. Collectively, thecontent marked as favorite indicates that “The Simpsons” is a concept inwhich the user has a strong interest.

In various embodiments, RSS feeds are created and updated withinformation on Alice's favorite content activity and Alice's friends'favorite content activity. Customizable feeds/alerts can also be createdso that Alice can, for example, be alerted when a certain number ofusers mark content containing the keyword Apple, a product titled MP3player, a new movie, etc. as favorite.

FIG. 6C is a flow chart illustrating an embodiment of a process forrecording a user's preference for content. The process begins at 672when an indication that a user has a first preference for the content isreceived. For example, at 672, Alice “diggs” story 450 by selectingregion 452. At 672, the content is associated with other content thathas also received an indication of the user's first preference. Forexample, at 674, story 450 is associated with Alice's other dugg content(by being added to the list of stories/etc. dugg by her). At 674, anindication that the user has a second for the content is received. Forexample, at 674, Alice designates story 450 as being her “favorite,”such as by selecting link 454. At 678, the content is associated withother content that has also received an indication of the user's secondpreference. For example, at 678, story 450 is associated with Alice'sother “favorite” content.

FIG. 7 is a flow chart illustrating an embodiment of a process forrecording a preference for a content contribution. The process begins at702 when an indication that a preference event has occurred is received.For example, when Alice selects digg box 406 shown in FIG. 4, herpreference is received at 702. Other examples of preference eventsinclude submitting a story, burying a story and commenting on a story.At 704, the preference event is associated with the content contributionand any associated scores are updated as applicable. For example, at704, Alice and story 402 are linked in database 112 and the digg scoreof story 402 is increased in database 112 from two to three. At 706,information associated with the user's profile is updated. For example,as described in more detail in conjunction with FIG. 6A, views ofAlice's digging history (including the friends' views of users who havelisted Alice as a friend) are updated to include the dugg story and anindication that Alice dugg it. Any RSS files associated with her profileand the profiles of those who have her listed as a friend will also beupdated as appropriate.

Visualizations

FIG. 8A illustrates an embodiment of a visualization interface. Theexample shown is an implementation of a portion of website 116 asrendered in a browser. In this example, interface 800 (also referred toherein as the digg “spy” interface and a “ticker” interface) isconfigured to present a real time visualization of preference eventsoccurring on preference system 102.

In the example shown, a user such as Alice can specify which stories tospy on. For example, she can spy on all stories (802), stories whichhave not yet been promoted (804), or just promoted stories (806).Further specification of a subset of stories can also be applied, asapplicable. For example, in various embodiments, a user can specify akey word that must be present in all stories being spied upon, and/orspy on stories in specified categories (not shown), and/or spy on eventstaken by friends only.

Additionally, a user can specify the types of preference events to bespied upon. In the example shown, Alice has checked (would like to see)all types of activity—new story submissions (indicated by icon 810),diggs (indicated by icon 812), buries (indicated by icon 814) andcomments (indicated by icon 816).

One way of implementing the visualization shown in FIG. 8A is asfollows. As a preference event occurs, it is recorded in database 112.Maintained within database 112 are a main database table and foursmaller tables 114—one for each type of event. The event is alsorecorded (either concurrently with, or on a periodic basis such as byway of an update function) in the respective smaller table thatcorresponds with the event. In some embodiments, filtering is applied sothat, for example, only commenting of registered users is recorded inthe comment table but all commenting is recorded in the main table. Aflag in the main database (e.g., a “do not report this to spy” flag) canalso be set to indicate whether information associated with a particularstory or user should be copied to the smaller tables 114. Alice is atypical user whose diggs are recorded in the main database table, aswell as the smaller table that records only diggs.

When Alice first visits interface 800 with her browser, and on arecurring basis after that (such as every 20 seconds, or whenever thepool of events is running low), batches of information are retrievedfrom server 102 in a scope commensurate with the options selected (whichdocuments to spy on and for which activities). Specifically, the mostrecent content from each of the smaller tables 114 is retrieved fromserver 102 and stored locally, such as in Alice's browser. AsynchronousJavaScript and XML (Ajax) components in interface 800 cause theinformation to displayed to Alice, for example, at a rate of one eventper second, depending on which information she would like to view. Insome embodiments, Alice can control the speed of the display, such asthrough playback controls 808.

In some cases, such as with heavy digging activity, there may besufficiently more than 20 diggs occurring site-wide during the twentysecond interval between the times that Alice's browser fetches a newbatch of digging information. Thus, after twenty seconds have elapsed,system 102 may have recorded 200 digg events—significantly more than the20 digg events that Alice periodically fetches. In some embodiments,only the most recent 20 actions are fetched. Thus, every twenty seconds,Alice requests the 20 most recent events and will never see anyintervening events.

In other embodiments, the number of events fetched adjusts in accordancewith the speed with which the events are occurring. In such a case, allof the events are fetched and the rate with which they are displayed issped up (showing one every tenth of a second if there are 200) or sloweddown (showing one every five seconds if there are only four) asappropriate. In some embodiments, a sampling of activity is takenthroughout the period so that if 200 events occur during the 20 secondinterval, a random sample of 20 will be supplied to Alice's browser.

In the example shown in FIG. 8A, Alice has been viewing interface 800for six seconds. Six events (830-840) are displayed, with the mostrecent (840) displayed at the top. As a new event is displayed, thealready displayed events are pushed down the display. Thus, for example,at time t1 (when Alice first began watching the interface), only event830 was presented. At time t2 (one second later), event 832 wasdisplayed above event 830, pushing event 830 down the screen. At time t3(one second after time t2), event 834 was displayed, pushing events 832and 830 each down one position, respectively.

By consulting the column descriptions (842), Alice can see that event830 was a submission of a new story (818), titled “Scientists DiscoverNew Type of Bird” (822), that the story was submitted by CharlieB (824),and that the story is currently unpromoted (826) with a digg score of 1(820). When event 832 appears in the display at time t2, Alice can seethat event 832 was a comment by Legolas on a story titled “How to Make aUSB Powered Alarm Clock” that currently has a digg score of 33 and hasbeen promoted out of the upcoming stories queue. At time t3, Alice cansee that David posted a new story titled “New Species of BirdDiscovered.” At time t4, David's story was reported as being a duplicatestory (828). The identity of a user burying something is not shown.Instead, only the reason for the bury (such as duplicate story,inaccurate story, old news, etc.) is shown. In other embodiments, otherinformation can be displayed, as applicable.

In FIG. 8A, the displayed digg count for a story is shown as what it wasat the time the event occurred. Thus, when event 838 (a digg of “How toMake a USB Powered Alarm Clock” by Bob) occurs, the digg count of thestory is shown as 33. The next time the story is dugg, the updated scoreis shown, such as when event 840 occurs. If the digg events arehappening sufficiently quickly that some of them are not displayed toAlice, she might see gaps between the scores. For example, if 50 diggsof the alarm clock story occur in the next few seconds, Alice may onlybe presented with the most recent digg and the updated total (e.g., 83diggs).

FIG. 8B illustrates an embodiment of a visualization interface. Theexample shown is an implementation of a portion of website 116 asrendered in a browser being used by Alice. In this example, interface850 (also referred to herein as a “stack” interface/visualization) isconfigured to present a visualization of newly submitted stories. Aftera new story is submitted, such as through the submission interfacedescribed in conjunction with FIG. 3, it is represented in interface 850as a green square falling from the top of the screen and landing at thebottom. Any stories already existing on the page (e.g., 858, 882, 856,854) are shifted to the left to make room for the new story (852). Insome embodiments, stories are removed from the left side to make spacefor stories on the right side. In other cases, the width of the storiesshown decreases to accommodate more stories as they are added to theinterface. The length of time that a user has been viewing interface 850is shown here as a timeline, with the time that Alice first startedviewing interface 850 on the left (866) and the current time on theright (868).

In the example shown, eleven new stories have been submitted since Alicebegan viewing interface 150. Statistical information such as the numberof stories submitted, the rate with which they are being submitted,etc., is indicated at 870. As preference events associated with thestories displayed in interface 850 occur, they are also indicated ininterface 850. For example, when a story is dugg, the event isrepresented by a digg icon, such as the one shown at 812 in FIG. 8Afalling from the top of the screen and onto the heap of thecorresponding story, increasing the size of the heap if it is a digg anddecreasing the size of the heap if it is a bury. For example, at 860, adigg of story 858 is shown falling down onto the story's graphicalrepresentation and will increase the height of the story box when itlands. A variety of indicators, such as colors and avatars can be usedto indicate the occurrence of preference events in addition to orinstead of the icons shown in FIG. 8A.

At 864, a bury of story 882 is shown falling down onto that story'sgraphical representation and will decrease the height of the story boxwhen it lands. In the example shown, the bury is indicated by the buryicon shown at 814 in FIG. 8A. The identity of the user burying the storyis not shown (as it can be in the case of other preference events), butby hovering her mouse over bury 864, Alice is shown a dialogue thatincludes the reason that the bury was submitted (e.g., “spam”).

In some embodiments, additional elements are included, such as theanimation shown at 880 (of a missile about to strike heap 882), andindications of who is taking the action. For example, diggs 860 and 862are being performed by friends of Alice. She is alerted to this fact bybubbles accompanying the digg action being performed that indicate theirnames and/or avatars. The look of interface 850 can be skinned in someembodiments—Alice can specify that she desires the interface to have amilitaristic theme, such as in the example shown, or other themes, suchas ones in which animals “eat” stories or multiply.

The relative popularity of newly submitted stories is indicated by therelative heights of the stories shown in interface 850. For example,story 884 is a very popular story, while story 856 is not.

In the example shown, only newly submitted stories are shown. Interface850 can also be scoped to represent other portions of activity. Forexample, Alice can specify that she wants to observe only actions takenby her friends (or groups of her friends), but across all stories, newor old. Alice can also specify that she wants to observe only actionsthat include a particular keyword, actions occurring only in particularcategories or subcategories, etc. Alice can also specify particularstories she wishes to monitor, such as by selecting a link on the page'spermalink that reads “add this story to my incoming view.” Alice canalso “pin” the stories shown in interface 850. When she hovers her mouseover a particular story shown in interface 850, one element that isrevealed is a pushpin icon which, if selected, causes the story toremain in region 886 of interface 850, and/or be added to a list offavorites (878).

A variety of graphical tools are shown on the left hand side ofinterface 850. They include charts of information such as which storiesin the last hour have been most popular 876, the relative rankings ofstories that Alice is monitoring (has pinned) 878, a more comprehensiveview (i.e., including information predating Alice's current interactionswith interface 850), etc. At 872, the story entry 170 of a story thatAlice hovers her mouse over, such as story 854, is displayed and she caninteract with the story entry 170 such as digging it or burying itaccordingly.

FIG. 8C illustrates an embodiment of a visualization interface. In theexample shown, a user may switch between different visualization styles(e.g., implementations of “stack” and “swarm”) by selecting amongchoices provided in region 888. The visualization shown in FIG. 8C hasmultiple modes which can be selected from in region 889. When “allactivity” is selected, all preference events occurring in all areas areincluded in the visualization. When “popular stories” is selected,stories that have been promoted to the front page are shown, arranged inthe order in which they were promoted. When “upcoming stories” isselected, the most recently submitted stories are shown. In someembodiments, information such as a color scale is used to help depictwhen newly submitted stories have associated preference events. Forexample, if a newly submitted story has twenty or more diggs, therepresentation of the story may be colored bright red, indicating thatthe story is rapidly gaining interest.

The interface shown in FIG. 8C also includes a region 893 in which auser may select between seeing a visualization depicting the activitiesassociated with individual stories (by selecting “Stories”) and avisualization depicting the aggregated activities associated with thecategories to which stories are assigned (by selecting “Topics”). In theexample shown in FIG. 8C, the “Topics” view is selected and thepreference events being visualized are relative to the topics ratherthan individual stories.

The interface shown in FIG. 8C also includes pause (890) and zoom (891)controls. The current amount of zoom is indicated in region 892. Byusing zoom control 891, groups of stories (e.g., the most recentstories) can be focused on, or the visualization can be pulled back fora broader view. Pause control 890 can be used, for example, to assist inmore readily focusing on a specific story when a great deal of activityis occurring and the visualization would otherwise change rapidly. Whenin the “popular stories” mode (889), the zoom control can be used asfollows. If the visualization is zoomed all the way out, the user isable to see the n most recently promoted stories, and get a sense ofwhich stories continue to have a significant amount of associatedpreference events, even if they are no longer on the front page. Thevisualization provides information on which stories are active, even ifthey were not recently submitted. The value of n can be configured bythe user and/or by a site administrator. An example default value of nis 100.

FIG. 8D illustrates an embodiment of a visualization interface. In theexample shown, Alice has selected a story from a stack visualizationinterface, such as by clicking on one of the stacks shown in FIG. 8B(e.g., 884, 856). In doing so, Alice is presented with additionalinformation about that story, such as who dugg it, how many comments ithas, etc. Links to the permalink page, etc., are also provided. In theexample shown in FIG. 8D, a sparkline-style graph is also provided thatshows a more detailed hour-by-hour display of activity on that story,including the frequency and magnitude of preference events. In variousembodiments the information in interface 894 is configurable. Forexample, while a default view may show the last 48 hours of activity,the user (or an administrator) may be able to specify additional ranges,and/or the default range may be selected based on how much activityassociated with the story has occurred. For example, a story with a lotof recent preference events may default to a 12 hour range, while an oldstory may show a histogram of all activity over all time.

FIG. 9 illustrates an embodiment of a visualization interface. Theexample shown is an implementation of a portion of website 116 asrendered in a browser. In this example, interface 900 is configured topresent a visualization of the genealogy of the diggs (also referred toherein as a “tree view”) of a story on preference system 102.

In the example shown, story 902 was originally submitted by the userDavid. When he successfully submitted the story, it appeared in hisprofile, as well as in the Friends History (e.g., at 610 of FIG. 6A) ofthe several people who have listed David as their friend. Suppose tenpeople have David as a friend, including users 904, 908, and 912 andseven users not pictured. After David submitted the story, friends 904,908, and 912 dugg story 902, either through their own friends' pages orthrough David's profile. They are displayed in interface 900 asconnected to David. Users who have David listed as a friend who did notdigg the story are not displayed in interface 900. Users 906 and 910 donot have David as a friend, but dugg the story through visiting hisprofile. As a result, they are also shown connected to David.

When users 904-912 dugg story 902, that action was recorded in theirrespective user profiles as well. Visitors to their profiles, and thosewho list them as friends who digg the story will be shown connected tothem, the way they are shown connected to David. If expansion tab 914 isselected, interface 900 will continue to provide detail down the tree(those who dugg story 902 through user 916, and so on).

One use of the tree view is that users can trace how their friendslearned about stories and meet new friends. For example, if Alicenotices that Bob diggs a lot of cryptography stories, she can determinewhere Bob diggs them from—does he submit the stories himself, or is hemainly digging stories submitted by CharlieB—and add new friends (suchas CharlieB) as appropriate.

FIG. 10 illustrates an embodiment of a visualization interface. Theexample shown is an implementation of a portion of website 116 reachedby selecting region 186 of FIG. 1B as rendered in a browser. In thisexample, Alice is viewing upcoming stories, which may be displayed in avariety of ways. If she selects region 902, Alice will be presented withupcoming stories in a format similar to that shown in the story window164 shown in FIG. 1B (including one or more story entries 170). In theexample shown, Alice has selected to view the upcoming stories in acloud view by selecting tab 904. In this view, the title of each storyin the upcoming queue is visualized as a function of the number of diggsit has. Stories with few diggs are shown in a very small font, and maybe colored in a subtle manner, such as by being displayed in grey.Stories with many diggs are shown in a very large font and may bedisplayed in another color, such as red or black. Stories dugg byfriends are also shown in a different color, such as green, irrespectiveof number of diggs. In some embodiments, additional information isreceived from the interface shown in FIG. 10 by taking an action such ashovering a mouse over a story title. In such case, information such asthe current digg score of the story, which if any friends have dugg thestory, and/or the story entry 170 of FIG. 1B is shown.

Which stories will appear in the cloud view can be configured, such asby selecting one or more categories to view or limiting the view tostories dugg by friends. The cloud view can also be sorted by a varietyof factors. As shown, the newest (most recently submitted) stories areshown at the top, and older stories are shown at the bottom of FIG. 10.If the stories were sorted by most diggs, then stories rendered in thelargest font would appear first and stories rendered in the smallestfont would appear last. Other sorting methods may also be used, such asby sorting by most or least comments.

FIG. 11A illustrates an embodiment of a visualization interface. Theexample shown is an implementation of a portion of website 116 reachedby selecting the appropriate portion of region 188 of FIG. 1B asrendered in a browser, and is an example of a swarm interface (alsoreferred to herein as a “swarm visualization”). In this example, Aliceis viewing upcoming stories. Users are shown represented by their avataricons or by more generalized shapes. As they digg a story, their icon isshown “swarming” around the story in real time—the avatar moves near thestory the user is digging, as do the avatars of the other userscurrently digging the story. In some embodiments, the size of the user'savatar (or other representation of the user) increases and decreasesbased on the number of stories they are currently digging.

In some embodiments, only recent activity is shown—such as diggs in thelast 10 minutes. Stories with more activities (such as diggs andcomments) will appear larger than stories with fewer activities. In someembodiments, additional information is received from the interface shownin FIG. 11A by taking an action, such as hovering a mouse over a storytitle. In such a case, information such as the current digg score of thestory, which, if any friends have dugg the story, and/or the story entry170 of FIG. 1B is shown. The links between stories can also be shown,indicating, for example, that several of the same people that dugg aparticular first story also dugg a second story, by connecting the twostories with a line. Indicators such as the color or width of the linecan show how strong or weak the connection is between the stories.

FIG. 11B illustrates an embodiment of a visualization interface. Theexample shown is an implementation of a swarm visualization. In theexample shown, stories are represented as circles, with the title of thestory in the center of the circle. Users “swarm” around a story whenthey indicate a preference for the story, such as by digging it (and/orcommenting on it, as applicable). Every time a story is dugg, thestory's circle increases in size. Thus, the bigger the circle, the moreactive the story is. In the example shown, story 1130 is very popular,while story 1132 is less popular. Story 1134 has very few associatedpreference events.

As users digg more stories, they move from circle to circle, and alsoincrease in size. For example, a very large user might represent aperson who is not taking much time to read stories, but is insteadmerely rapidly indicating preferences. In the example shown in FIG. 11B,the user “Bob” (1136) has recently indicated preferences for manystories, while other users (e.g., user 1138) are less active. In theexample shown, stories are initially randomly placed within theinterface. As preference events associated with the stories occur, theirpositions change depending on who is digging (commenting, etc.) on them.For example, stories that are closer together indicate that they arebeing dugg by the same users, and by hovering a mouse over the story,such connections between stories are revealed.

Different modes of the swarm visualization may be presented by selectingone of the options in region 1140. For example, if the “all activity” isselected, circles representing stories and diggers are quickly removedfrom display if no associated preference events are occurring/beingmade, respectively. When the “popular stories” mode is selected, thedisplay is initially loaded with the n stories most recently promoted tothe front page. As new stories are promoted, they appear in thevisualization, and the (n+1)th story is removed. The value of n may beconfigured, e.g., by a user or an administrator. In some embodiments nis 35. When the “upcoming stories” mode is selected, the n most recentlysubmitted stories each receive a circle. In some embodiments n is 30.

FIG. 11C illustrates an embodiment of a visualization interface. In theexample shown, Alice has selected a story from a swarm visualizationinterface, such as by clicking on one of the story circles shown in FIG.11B. In doing so, Alice is presented with additional information aboutthat story, such as who dugg it, how many comments it has, etc. Links tothe permalink page, etc., are also provided.

In the example shown in FIG. 11C, the lines between stories indicatecommon diggers between those stories. The more diggers in common that astory has, the thicker the line. For example, stories 1150 and 1152 haveconsiderably more common diggers (as indicated by line 1156) thanstories 1150 and 1154 do (as indicated by line 1158).

Alice may also override the default amount of time a particular storywill be displayed in (e.g., in the interface shown in FIG. 11B) byselecting either region 1150 or 1162 of the interface shown in FIG. 11C.Thus, for example, to prevent story 1150 from being removed when a newstory is displayed, Alice may select region 1160. To immediately removethe story from the interface irrespective of when it might otherwisehave been removed, Alice may select region 1162.

Additional Embodiments

In some embodiments, a plugin and/or add-on to a computer programproduct is used to provide digging (and/or burying, commenting, andsubmitting) functionality. The plugin/add-on is associated with aninterface to server 102, which may include functions that determinewhether a permalink already exists for the submission, and invokeprocessing of a new submission, a comment, etc., as appropriate.

For example, a plugin to a web browser (e.g., a Firefox extension) canbe configured to offer a user the ability to digg an item directly fromthe context in which it is encountered without having to visit thesubmission interface described in conjunction with FIG. 3 or a permalinksuch as the one shown in FIG. 4A. For example, a notification embeddedin a page or overlayed such as by the browser can indicate whether thepage a user is currently browsing has been submitted as a storycontribution yet. If not, a user can interact with the notification,such as by clicking on an interface that reads, “this page has not yetbeen submitted to digg.com, submit it now.” Similarly, if the page hasalready been submitted, such as by a different user, the notificationmay take a variety of forms, such as an overlay of the current diggscore (172) and a digg box, or a change, for example, in the backgroundcolor, or some other element of the page.

Configurable dropdowns and/or overlays can also be provided to alert auser of certain activity. For example, the user can set an alert toreceive notification when new stories having certain keywords aresubmitted to server 102. Notification can also be provided for friends'digging activities as they occur, such as that a friend has just dugg astory or commented on a product.

As used herein, content contributions are pointers to content (e.g.,news articles and podcasts) that is stored outside of preference system102, typically by a third party. In some embodiments, users submit thecontent itself (e.g., the full text of articles, and the audio file)rather than or in addition to a pointer to the content, and thetechniques described herein are adapted accordingly. The terms“content,” “content contribution” and “pointers to content” are usedherein interchangeably. As described in more detail below, contentcontributions are not limited to news articles. Other content (such asproducts, services, songs, sounds, photographs, and video) can besubmitted, dugg, buried and commented on, and the techniques describedherein can be adapted as appropriate. Preference events taken on thosetypes of content may likewise be associated with a profile and sharedwith friends in a manner similar to that described, for example, inconjunction with FIG. 6A.

FIG. 12A is an example of a content contribution. The example shownrepresents a restaurant submission. The name of the restaurant (1200) isincluded, as is information such as who submitted the restaurant, theURL of the restaurant, the type of cuisine it serves (1202), and thegeneral location of the restaurant (1204). Users may perform suchactions as searching for restaurants by cuisine type and/or location,and limiting results to ones having a threshold number of diggs.Restaurants having no or few diggs can be displayed as “upcomingrestaurants,” separated from “promoted restaurants” which have diggscores exceeding a threshold. Users can also supply additionalinformation about their preferences for the reference, such as bysupplying one or more tags (1202) that indicate attributes such as“ambiance” or signature dishes. As described in more detail below, whichfields/tags are collected at submission time (and which, if any, can beadded subsequently) and shown can be configured as appropriate dependingon the type of content. For example, in the case of a product, a stockphoto of the product may be included.

FIG. 12B illustrates an embodiment of an interface to a preferencesystem. In the example shown, the interface unifies a user's preferencefor things across multiple genres of content. For example, the user candigg for news (1250), videos (1252) and restaurants (1254) all throughthe same interface. As described in more detail below, the friendsfeatures described above can also be used in conjunction with othertypes of content contributions. For example, using the interface shownin FIG. 12B, a visitor to Alice's profile can learn which news storiesshe's been digging as well as learn which restaurants she diggs ordoesn't digg. Similarly, Alice can customize the views of each of thetabs (1250, 1252, 1254) to display only restaurants her friends haveagreed on, restaurants nearby (e.g., by selecting a region on a map orentering a ZIP code) that at least one friend has dugg, etc.

FIG. 12C illustrates an embodiment of an interface to a preferencesystem. In the example shown, digging functionality has been combinedwith mapping functionality. When a user searches a map, such as aweb-based map service, for nearby restaurants, entries on the mapinclude an indication of the number of diggs a business has had and theability to digg or comment on the business directly from the mapinterface.

FIG. 13A illustrates an embodiment of an interface to a preferencesystem. The example shown is an implementation of a portion of website116 which includes the ability to submit, digg and comment on products(including software), as rendered in a browser. In this example, Alicehas selected to view products agreed on by her friends (1322).

Alice can submit a new product review by selecting portion 1302 ofinterface 1300. She can view products in one or more categories byselecting the appropriate portion of region 1304. Portion 1306 ofinterface 1300 displays the recent activities of Alice's friends in adashboard format.

Region 1326 of interface 1300 indicates that four of Alice's friendshave dugg product 1324, the ACME MP3 player. Alice can also see which ofher friends have dugg product 1324 by hovering her input device over thedigg score box of product 1324. In some embodiments, Alice can interactwith region 1326, such as by being presented with a dialogue that offersto send an email to all of her friends listed in the region. In someembodiments, additional actions can be taken with product 1324. Forexample, Alice may be presented a “buy this product now” icon or link.

All of the views shown in FIG. 13A can be syndicated as RSS feeds byselecting RSS link 1320 on the appropriate page view. For example, ifAlice is a professional critic, users and those who choose not to useweb site 116 on a regular basis can syndicate comments that she makes onproducts, etc.

In some embodiments, profile visitors (including Alice) are presentedwith the option to search (1308) all of site 116 for product keywords(1310), search Alice's diggs for product keywords (1312), and/or searchdiggs made by Alice's friends for product keywords (1314). For example,a visitor to Alice's profile can search for MP3 players that she hasdugg or commented on. In some embodiments, search interface 1308includes the ability to filter results on meta information such asregions for DVDs, languages for books, etc. In some embodiments, views(and searches) can be limited by other factors, such as location(distance from Alice), availability (whether a product is in stock andhow quickly it can arrive), etc.

FIG. 13B illustrates an embodiment of an interface to a preferencesystem. The example shown is, as rendered in a browser, animplementation of a portion of website 116 that includes the ability tosubmit, digg and comment on products. In this example, Alice hasselected to view products in the category, MP3 player, from a larger setof categories, such as those listed in region 1304 of FIG. 13A.

In the example shown, each product listing (1302, 1304) includes aphotograph of the MP3 player (1306), as well as a digg score/digg box(1308), title, description, etc. (1310). The MP3 players shown in thisexample are sorted by popularity.

On the right hand side are assorted graphs (1312, 1314) of informationassociated with the products shown. Graph 1312 compares the popularity(e.g., digg scores, number of comments recently made) of different MP3players against each other over time so that trends such as which onesare gaining in popularity and which ones are decreasing in popularitycan be visually determined.

In the example shown, the Acme F242 player is more popular than the Beta10 player. In some embodiments, the frequency with which a user visitspreference system is considered when determining the popularity of aproduct. For example, suppose the Beta 10 player has 165 diggs, 25 ofwhich were made by users who have not visited the preference system in 3months. In some embodiments, the diggs of those 25 users are expired.The product will remain listed in the absent user's profiles, but theirdiggs will not be included when calculating the popularity of theproduct.

Users also have the ability to undigg a product to indicate that they'vemoved onto something new. For example, suppose Alice currently has aBeta 10 player and is interested in upgrading. If she purchases an AcmeF242, she can visit her profile to undigg the Beta 10 and digg the AcmeF242. Her actions—undigging the Beta 10 and digging the Acme F242instead—will also be reflected in graph shown at 1312. For example, onthe day that she undiggs the Beta 10, its position along the verticalaxis will be decreased. On the day that she diggs the Acme F242, theAcme F242's position on the graph will similarly increase.

Graph 1312 also includes indications of the individual users who aretaking digging and undigging actions. For example, when Alice hovers hermouse over region 1318, she can see that a user, Mark, dugg the AcmeF242. Indications of actions taken by her friends are also included ongraph 1312. For example, regions associated with friends' diggs of theAcme F242 are highlighted in green, or with avatars or other indicatorsthat her friends have indicated preferences at a particular time. Forexample, Alice can use graph 1312 to determine that David dugg the Acme242 two months after Charlie dugg the Beta 10.

The information shown in FIG. 13B can also be generated based on one ormore searches in addition to or instead of tabbed browsing. For example,Alice could perform a search of “popular MP3 players at least one of myfriends owns” and see the information shown in FIG. 13B as a result.

In some embodiments, demographic information is displayed. For example,in graph 1314, the popularity of a particular MP3 player is broken downby assorted groups such as teens and adults, or girls and boys.Demographic information can similarly be included in a search so that,for example, a parent shopping for a present for his or her child canlocate the “hottest MP3 players among teenagers this week,” and the“most popular movie for women aged 20-30,” through a search interfaceconfigured to accept such queries.

FIG. 14 illustrates an embodiment of an interface to a preferencesystem. The example shown is an implementation of a portion of website116 which includes the ability to submit, digg and comment onphotographs and video, as rendered in a browser. In the example shown,photograph 1402 was dugg by a friend, as indicated by banner 1404. Byselecting digg box 1406, a visitor can indicate a preference for thephotograph shown. In some embodiments, visitors indicate theirpreference for content such as video 1408 by selecting an icon such asicon 1410.

The content shown in interface 1400 can be presented in a variety ofways. For example, video content may be represented as an icon, such asthe filmstrip icon shown at 1408. A screen shot of the first frame ofthe video may also be shown, and interactions such as hovering a mouseover region 1408 could trigger actions such as causing the video to beplayed in the browser.

In some cases, it may not be possible to embed the content directly intothe interface shown in FIG. 14. In such a case, the video is shown in aformat similar to story entry 170 (1416), and a preview button 1414 isincluded. When preview button 1414 is selected, a video player 1412automatically slides out in which the video can be displayed.

Permalink pages such as the one shown in FIG. 4A can be adapted forphotograph and video content as appropriate, and users may comment,blog, and take other actions with respect to visual and other content(such as songs) as appropriate.

Audience Platform

Using the techniques described herein, a community is given anopportunity to pose questions (e.g., to individuals)—without the use ofeditors. In the following example, suppose that a featured guest (e.g.,the politician, “Joe Smith”) has already been selected as aninterviewee. A permalink page for the interview is created, eithermanually by an administrator of system 102, or automatically, in amanner similar to the creation of the story permalink page shown in FIG.4A, or as otherwise appropriate.

FIG. 15 illustrates an embodiment of a process for processing questions.In some embodiments the process shown in FIG. 15 is performed bypreference system 102. The process begins at 1502 when a question isreceived. For example, a question is received at 1502 when a user ofsystem 102 types a question into a text box, as described in more detailbelow. In various embodiments, processing such as checking forduplicates (and offering to show the user the existing question) andchecking for offensive words is optionally performed. Questions can alsobe received from third party sources, such as via a third party website,an application, or other applicable source, such as through use of anAPI.

At 1504, a preference event (e.g., a digg or bury) is received for thequestion. At 1506, a score is determined for the question based on thereceived preference event. Once an appropriate triggering event occurs(such as a deadline being reached), a set of questions is automaticallyselected to be presented to the interviewee.

FIG. 16 illustrates an embodiment of an interview permalink. The exampleshown is an implementation of a portion of website 116 as rendered in abrowser. Users are able to enter new questions for Joe Smith byproviding them in region 1602 and selecting “submit.” As with othercontent described above, users are able to digg/bury/comment onpreviously submitted questions using the interface shown. Users are alsoable to indicate problematic questions (e.g., those that areinappropriate, duplicate, etc.). Information about Joe Smith, such ashis picture and a short biography is included. Also included in theinterface shown in FIG. 16 is an indication that the interview with JoeSmith is sponsored by “Newspaper News Corp.” In various embodiments,sponsors (e.g., promoting an upcoming movie, a political candidate) areable to pay (e.g., the owner of system 102) to have a specificindividual or group of individuals interviewed. Advertisements promotingthe interview (and, for example, directing those that click onadvertisements to the interview permalink page) can be purchased andplaced within site 116 and also on third party sites as applicable.

In various embodiments, questions can also be submitted in otherformats. For example, an alternate version of the interface shown inFIG. 16 includes an additional box in which users may provide a URL(leading to an audio or video file that represents their question), alocation of a file on disk, or audiovisual capture functionality (e.g.,to capture audio from a computer microphone). If audiovisual questionsare submitted, system 102 processes the data and makes it available toother users so that they can view/listen to the questions, and canprovide transcripts for others. In some embodiments, transcripts ofaudiovisual submissions are automatically made (e.g., using third partytranscript services). If audiovisual questions are among thoseultimately selected for presentation to an interviewee, in someembodiments system 102 is configured to automatically package theaudiovisual questions together and make them available to theinterviewee, in some cases negating the need for a live host.

The interview permalink page shown in FIG. 16 includes an indication1604 of when the question solicitation period will end. In this example,users have 1 day and 20 hours left to submit questions and/or to providefeedback on the questions posted by other users. In various embodiments,other rules can be used to end the ability of users to submit questionsfor consideration. For example, instead of relying on a time-baseddeadline, the receipt of a threshold number of questions (e.g., 100),the receipt of a threshold number of diggs, the receipt of a thresholdnumber of diggs relative to a threshold number of questions (e.g., 20questions, each having at least 100 diggs) or other triggering eventscan be used, as applicable. In various embodiments, the selectioncriteria are configurable. For example, if an interview is sponsored byan advertiser, the advertiser can specify that none of the selectedquestions be controversial, that none of the questions include offensivewords, that none of the questions mention a competitor by name, etc. Thesponsor can also specify that an additional “n” questions be included asalternates. For example, if the sponsor intends to ask 10 questions, thesponsor may specify that the top 15 questions be determined at thetriggering event, to give the sponsor some flexibility in conducting theinterview.

The interface shown in FIG. 16 allows users to customize their view ofthe interview permalink page. For example, they can choose to see all827 questions, they can choose to see only the questions they havesubmitted themselves, and they can also elect to see questions submittedby their friends. By selecting various options in drop down 1606, userscan elect to sort the questions in various ways, such as by newestfirst.

FIG. 17A illustrates an embodiment of a portion of an interviewpermalink. In the example shown, a user has elected to sort thequestions by “most controversial” first (1702). These questions are onesfor which a significant number of both positive (e.g., digg) andnegative (e.g., bury) preference events have been received. In addition,FIG. 17A illustrates that users may comment on questions by selectingthe “Reply” option 1704.

FIG. 17B illustrates an embodiment of a portion of an interviewpermalink. In the example shown, a user has elected to sort thequestions by “most dugg” first.

As mentioned above, when a triggering event occurs (e.g., a deadline isreached), a subset of questions is automatically selected from the setof received questions based on received preference events. In someembodiments, the selected questions are those having the highest diggscores. In other embodiments, a mix of questions can be specified, toinclude the 10 most dugg questions and the 5 most controversialquestions, for example. Other rules can also be specified, such as the10 most dugg questions and the 5 most controversial questions that alsohave at least 100 diggs. A host then interviews the interviewee from thequestions selected. In various embodiments, the interview is shown live(e.g., streamed on site 116). An archive copy of the interview and/or atext transcript are then made available on the corresponding interviewpermalink page for future visitors to that interview permalink page. Insome embodiments, instead of a live, hosted interview, the interviewquestions are sent to the interviewee in text form and the intervieweeresponds, also in text form, and the results are automatically includedin the interview permalink page. The selected questions can also bepresented to the interviewee as part of a live text-based chat,facilitated by system 102.

FIG. 18 illustrates an embodiment of a portion of an interface to apreference system. In the example shown, a list of links to allinterview permalink pages on system 102 is provided. Included in thelist is the interview permalink illustrated in FIG. 16 (for which usersmay still provide questions) and completed interviews (for which usersmay view questions and comments, as well as read the interviewtranscript and/or watch the interview footage). In various embodiments,interview permalinks are indexed by category (e.g. politics forpolitical interviewees, entertainment for movie stars) and/or areaccessible via links such as are shown in region 160 of FIG. 1B.

In addition to an environment such as is shown in FIG. 1, the audienceselection and preference features described herein can also be deployedin other environments, such as in a standalone fashion on a third partytelevision station web page, on a third party newspaper web pageconfigured to communicate with system 102, etc. For example, the editorof a well-known newspaper can use the techniques described herein to beprovided electronically with top suggestions of what questions to poseto interviewees as part of a print-based interview. In such a scenario,the editor of the newspaper could have the appropriate functionality beprovided by the newspaper's website and/or the newspaper's website couldobtain portions of the processing service from system 102. For example,system 102 can be configured to include a custom module that allows thenewspaper editor to manually specify deadlines, interviewees, etc.,while still having system 102 allow users to contribute/comment oninterview questions and automatically select the questions to be askedby the newspaper editor.

As yet another example, in some embodiments questions can be submittedvia (and/or voted on) via a standalone application such as anapplication installed on a cellular phone. The cellular phone'smicrophone and camera (if applicable) can be used by the user to submitaudiovisual questions, if desired. Submissions of and interactions withquestions can also occur through the use of an API, browser plug-in,etc.

As mentioned above, in some cases the featured guest is selected by aneditor or otherwise directly provided. In other cases, the targetinterviewee can also be selected using the techniques described herein.For example, users can be provided an interface into which they cansubmit the names of prospective guests. Other users can digg or burytheir suggestions. Examples of prospective featured guests includeleaders and other individuals across diverse topics including technologyluminaries, environmentalists, politicians, scientists, entrepreneurs,musicians and filmmakers.

FIG. 19 illustrates an embodiment of a process for selecting aninterviewee candidate. In some embodiments, the process shown in FIG. 19is performed by preference system 102. The process begins at 1902 whenan identification of a candidate is received. For example, anidentification is received at 1902 when a user of system 102 providesthe name “John Johnson” into a submission form provided by system 102.Optionally, information about the candidate such as a category (e.g.,scientist, celebrity), a representative URL for the candidate, etc., isalso solicited on the form. Various processing such as checking forduplicates or disambiguating common names is optionally performed (e.g.,by matching the supplied name against existing permalink pages andoffering to direct the user appropriately). Identifications ofcandidates can also be received in other ways. For example, instead ofor in addition to typing the name of the individual into a form, userscan also provide URLs (e.g., to the candidate's official website, to aWikipedia page about the candidate, to the candidate's social networkingpage) that are used to uniquely identify the candidate. Duplicatechecking can be optionally performed on the supplied URLs, asapplicable.

At 1904, a preference event (e.g., a digg or bury) is received for thecandidate. At 1906, a score is determined for the candidate intervieweebased on the received preference event. Once an appropriate triggeringevent occurs (such as a deadline being reached), an interviewee isautomatically selected.

The process shown in FIG. 19 can be adapted to select interviewees,hosts, and groups/panels of interviewees and hosts as applicable.Additionally, the processes of FIGS. 19 and 15 can be combined. Forexample, in some embodiments when a candidate is identified at 1902, apermalink page for the candidate is created (if one does not alreadyexist). If that candidate is selected as an interviewee, the permalinkpage for that candidate can be configured to automatically acceptquestions (and configured not to accept questions unless/until thecandidate is selected as an official interviewee).

FIG. 20 illustrates an embodiment of a candidate selection page. Theexample shown is an implementation of a portion of website 116 asrendered in a browser. Users are able to indicate preferences forcandidates (e.g., received at 1902 in the process of FIG. 19) byselecting region 2002. When the triggering event occurs (e.g., two dayspass), the candidate with the most diggs is automatically selected forinterview, and a permalink page corresponding to the candidate willautomatically be configured to accept questions.

The techniques herein can be adapted to allow users to nominatecandidate awardees (e.g., for best actress, best new single/album, bestrestaurant, product of the year) and also to provide preferencefeedback/comments on those award nominees.

FIG. 21 illustrates an embodiment of a process for selecting an awardeecandidate. In some embodiments the process shown in FIG. 19 is performedby preference system 102. The process begins at 2102 when anidentification of a candidate is received. For example, anidentification is received at 2102 when a user of system 102 providesthe name of an actress, “Star Starlett,” into a submission form providedby system 102. Optionally, information about the candidate, such as acategory (e.g., best actress), a representative URL for the candidate,etc., are also solicited. Various processing such as checking forduplicates or disambiguating common names is optionally performed (e.g.,by matching the supplied URL against information associated withexisting permalink pages). Identifications of candidates can also bereceived in other ways. For example, system 102 can be configured towork in cooperation with a third party movie site which stores detailedinformation about movies, actors, directors, etc. Buttons placed on thethird party movie site can be configured to automatically displayappropriate messages such as “submit this actress” or “digg thisactress's performance” based on whether or not the corresponding actresshas already been identified at 2102.

At 2104, a preference event (e.g., a digg or bury) is received for thecandidate. At 2106, a score is determined for the candidate awardeebased on the received preference event. Once an appropriate triggeringevent occurs (such as a deadline being reached), an awardee isautomatically selected.

FIG. 22 illustrates an embodiment of a third party website. In theexample shown, a third party movie site (“ACME Movie Site”) has beenconfigured to work in cooperation with system 102 to allow users of themovie site to nominate actors (and actresses, films, directors, editors,soundtracks, etc.) for various annual awards, and also to providepreference feedback for nominees. By selecting region 2202, a user ofthe movie site is submitting an identification (received at 2102 of theprocess shown in FIG. 21) to system 102. If an identification for theactress has already been received, the message “digg my performance” orsimilar text would be displayed in region 2202.

In various embodiments, award categories (e.g., best actor, bestdirector, best restaurant in New York) are manually configured by anadministrator of system 102 or other appropriate party. Each categoryreceives its own permalink page and users of system 102 can suggestwinners/provide preference feedback through use of an interface similarto that shown in FIG. 16. For example, for a “best restaurant in NYC”award, users can submit restaurant names in a region similar to region1602 and could digg or bury existing entries, sort by mostcontroversial, etc., in an analogous manner to the techniques describedin conjunction with FIG. 16.

FIG. 23 illustrates an embodiment of an interface to a preferencesystem. The example shown is an implementation of a portion of website116 as rendered in a browser. In the example shown, an indication thatquestions are currently being accepted for an interview of Joe Smith isdisplayed in region 2302, with other content contributions displayedbelow. In various embodiments, interview entries are automatically shownalongside recently “promoted” content when certain events occur withrespect to the interview. For example, when the period for submittingquestions opens, the interview permalink page is automatically“promoted” so that users of site 116 know that they are able to startasking questions. One day before the period for submitting questionsends, the interview permalink page is automatically “promoted” again sothat users of site 116 know that they should get their questions inbefore the deadline. On the day of the interview, the interviewpermalink page is automatically “promoted” again so that users of siteknow that they can watch a live video feed of the interview, etc.

Although the foregoing embodiments have been described in some detailfor purposes of clarity of understanding, the invention is not limitedto the details provided. There are many alternative ways of implementingthe invention. The disclosed embodiments are illustrative and notrestrictive.

What is claimed is:
 1. A system, comprising: a processor configured to:serve a web page identifying a selected interviewee; and during aninterview with the selected interviewee: receive via the web page afirst question directed to the interviewee; display the first questionin the web page; receive from multiple viewers, as they view the webpage, a first plurality of preference events associated with the firstquestion; calculate a score for the first question based at least inpart on the first plurality of preference events; and determine, basedon the calculated score, whether to pose the first question to theinterviewee; and a memory coupled to the processor and configured toprovide the processor with instructions.
 2. The system of claim 1,wherein the processor is further configured to: rank multiple questionsreceived via the web page, including the first question, based on theircontroversy; wherein each of the preference events associated with thefirst question is one of: a positive preference for the first question;and a negative preference for the first question; and wherein thecontroversy of the first question is different from the calculated scoreand is inversely proportional to the difference between a total numberof positive preferences of the first question and a total number ofnegative preferences of the first question by the multiple viewers. 3.The system of claim 1, wherein the score comprises a rank.
 4. The systemof claim 1, wherein at least one preference event is an indication of apositive preference.
 5. The system of claim 1, wherein at least onepreference event is an indication of a negative preference.
 6. Thesystem of claim 1, wherein the processor is further configured toreceive, during the interview, an indication of a problem associatedwith the first question.
 7. The system of claim 1, wherein the processoris configured to receive the first question as text data.
 8. The systemof claim 1, wherein the processor is configured to receive the firstquestion as video data.
 9. The system of claim 1, wherein the processoris configured to receive the first question as audio data.
 10. Thesystem of claim 1, wherein: the first question is received from a firstweb site; and the score for the first question is displayed on a secondweb site.
 11. The system of claim 1, wherein: the first question isreceived from a first web site; and at least one preference eventassociated with the first question is received from a second web site.12. The system of claim 1, wherein at least one preference event isreceived from a mobile device.
 13. The system of claim 1, wherein theprocessor is further configured to: during the interview: receive asecond question via the web page; display the second question in the webpage; receive from the multiple viewers, as they view the web page, asecond plurality of preference events associated with the secondquestion; and rank the first question and the second question based onthe first plurality of preference events and the second plurality ofpreference events.
 14. The system of claim 1, wherein the processor isfurther configured to: during the interview: receive additionalquestions and additional preference events associated with theadditional questions until a triggering event occurs.
 15. The system ofclaim 14, wherein the triggering event is an expiration of a deadline.16. The system of claim 14, wherein the triggering event is receipt of athreshold number of questions.
 17. The system of claim 14, wherein thetriggering event is receipt of a threshold number of preference events.18. A method, comprising: serving a web page identifying a selectedinterviewee; and during an interview with the selected interviewee:receiving via the web page a first question directed to the interviewee;displaying the first question in the web page; receiving from multipleviewers, as they view the web page, a first plurality of preferenceevents associated with the first question; calculating, with aprocessor, a score for the first question based at least in part on thefirst plurality of preference events; and determining, with theprocessor and based on the calculated score, whether to pose the firstquestion to the interviewee.
 19. The method of claim 18, furthercomprising: ranking multiple questions received via the web page,including the first question, based on their controversy; wherein eachof the preference events associated with the first question is one of: apositive preference for the first question; and a negative preferencefor the first question; and wherein the controversy of the firstquestion is different from the calculated score and is inverselyproportional to the difference between a total number of positivepreferences of the first question and a total number of negativepreferences of the first question by the multiple viewers.
 20. Themethod of claim 18, wherein the score comprises a rank.
 21. The methodof claim 18, wherein at least one preference event is an indication of apositive preference.
 22. The method of claim 18, wherein at least onepreference event is an indication of a negative preference.
 23. Themethod of claim 18, further comprising, during the interview: receivingan indication of a problem associated with the first question.
 24. Themethod of claim 18, wherein the first question is received as text data.25. The method of claim 18, wherein the first question is received asvideo data.
 26. The method of claim 18, wherein the first question isreceived as audio data.
 27. The method of claim 18, wherein: the firstquestion is received from a first web site; and the score for the firstquestion is displayed on a second web site.
 28. The method of claim 18,wherein: the first question is received from a first web site; and atleast one preference event associated with the first question isreceived from a second web site.
 29. The method of claim 18, wherein atleast one preference event is received from a mobile device.
 30. Themethod of claim 18, further comprising, during the interview: receivinga second question via the web page; displaying the second question inthe web page; receiving from the multiple viewers, as they view the webpage, a second plurality of preference events associated with the secondquestion; and ranking the first question and the second question basedon the first plurality of preference events and the second plurality ofpreference events.
 31. The method of claim 18, further comprising,during the interview: receiving additional questions and additionalpreference events associated with the additional questions until atriggering event occurs.
 32. The method of claim 31, wherein thetriggering event is an expiration of a deadline.
 33. The method of claim31, wherein the triggering event is receipt of a threshold number ofquestions.
 34. The method of claim 31, wherein the triggering event isreceipt of a threshold number of preference events.
 35. A computerprogram product embodied in a non-transitory computer readable storagemedium and comprising computer instructions for: serving a web pageidentifying a selected interviewee; and during an interview with theselected interviewee: receiving via the web page a first questiondirected to the interviewee; displaying the first question in the webpage; receiving from multiple viewers, as they view the web page, afirst plurality of preference events associated with the first question;calculating a score for the first question based at least in part on thefirst plurality of preference events; and determining, based on thecalculated score, whether to pose the first question to the interviewee.